70 Works

Additional file 9 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio...

DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Abstract Background COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS. Methods We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A...

Additional file 2 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 2: Table S2. Summary of different models tested for estimating differences between controls and COVID-19 patients for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p.value for each tested model for each cell type are shown. The following models were tested, mod1; Age and ethnicity as covariates, mod2; age as a covariate, mod3; ethnicity as a covariate, mod4; no covariates.

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Abstract Background Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly...

Additional file 9 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 9: Correlation of 3 ir-lncRNA signature with immune subpopulations across tumor types. Pearson correlation heatmap between immune cell subpopulation enrichment scores and 3 ir-lncRNA scores.

Additional file 2 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 2: Differentially expressed lncRNAs in TCGA-BRCA

Additional file 2 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 2: Differentially expressed lncRNAs in TCGA-BRCA

Additional file 4 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 4: Canonical pathways, diseases and functions associated with the 127 proxy protein-coding genes.

Additional file 1 of Thematic analysis of the raters’ experiences administering scales to assess depression and suicide in Arab schizophrenia patients

Iman Amro, Suhaila Ghuloum, Samer Hammoudeh, Yahya Hani, Arij Yehya & Hassen Al-Amin
Additional file 1.

Thematic analysis of the raters’ experiences administering scales to assess depression and suicide in Arab schizophrenia patients

Iman Amro, Suhaila Ghuloum, Samer Hammoudeh, Yahya Hani, Arij Yehya & Hassen Al-Amin
Abstract Background This study aimed to enhance the cultural adaptation and training on administering the Arabic versions of the Calgary Depression Scale in Schizophrenia (CDSS) and The International Scale for Suicidal Thinking (ISST) to Arab schizophrenia patients in Doha, Qatar. Methods We applied the qualitative thematic analysis of the focus group discussions with clinical research coordinators (CRCs). Five CRCs met with the principal investigator for two sessions; we transcribed the conversations and analyzed the content....

Additional file 1 of Microbiological and clinical characteristics of invasive Group B Streptococcal blood stream infections in children and adults from Qatar

Maisa Ali, Mohammed A. Alamin, Gawahir A. Ali, Khalid Alzubaidi, Bashir Ali, Abdellatif Ismail, Joanne Daghfal, Muna Almaslamani & Hamad Abdel Hadi
Additional file 1. Appendix 1: Hospitals Covered by Hamad Medical Corporation (HMC) in Qatar. Appendix 2: Antibiotic Susceptibility and D Tests for 196 invasive GBS bacteraemia isolates.

Additional file 10 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 10: Table S10. Description of the eight genes that are predictors of mortality. Data were collected from Gene Ontology (GO) to identify the functional annotation of each gene and recently published COVID-19 related articles to highlight the role of each gene in relation to COVID-19.

Additional file 4 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 4: Table S4. Summary of differentially methylated pathways detected between COVID-19 patients and controls based on CpG sites.

Additional file 2 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 2: Table S2. Summary of different models tested for estimating differences between controls and COVID-19 patients for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p.value for each tested model for each cell type are shown. The following models were tested, mod1; Age and ethnicity as covariates, mod2; age as a covariate, mod3; ethnicity as a covariate, mod4; no covariates.

Additional file 3 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 3: Table S3. Summary of identified differentially methylated CpGs between COVID-19 patients and controls. A. All significant CpGs B. Variable description from Table S2A. C. Significant CpGs from genes previously described as COVID-19 important [1]. D. Functional annotation of genes from Supplemental table 3C.

Additional file 6 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 6: Table S6. Analysis of dead and recovered+A3 COVID-19 patients for immune cell proportions. A. Summary of different models tested for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p-value for each tested model for each cell type are shown. The following models were tested, mod1; Age + MV days + Gender + ICU LoS + ECMO + Nosocomial infections, mod2; Age + Gender + ICU LoS + ECMO +...

Additional file 8 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 8: Table S8. Description of 27 genes from 49 differentially methylated CpGs between survived and dead patients over four time points. A summarized description of the 27 genes obtained from Supplementary Table 7B, collected from Gene Ontology (GO) to identify the functional annotation of each gene and recently published COVID-19-related articles to highlight the role of each gene in relation to COVID-19.

Additional file 8 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 8: Table S8. Description of 27 genes from 49 differentially methylated CpGs between survived and dead patients over four time points. A summarized description of the 27 genes obtained from Supplementary Table 7B, collected from Gene Ontology (GO) to identify the functional annotation of each gene and recently published COVID-19-related articles to highlight the role of each gene in relation to COVID-19.

Prevalence, Outcome, and Optimal Management of Free-Floating Right Heart Thrombi in the Context of Pulmonary Embolism, a Systematic Review and Meta-Analysis

Wanis H. Ibrahim, Fateen Ata, Hassan Choudry, Huzaifa Javed, Khaled M Shunnar, Abdullah Shams, Abdullah Arshad, Adel Bosom, Mohammed H.A. Elkahlout, Bisher Sawaf, Shahda M.A. Ahmed & Tinuola Olajide
Free-floating right-heart thrombus (FFRHT) in the context of a pulmonary embolism (PE) is a rare but serious encounter with no guidelines addressing its management. We performed a systematic review and meta-analysis addressing prevalence, clinical behavior, and outcomes of FFRHT associated with PE. Among the included 397 patients with FFRHT and PE, dyspnea was the main presenting symptom (73.3%). Obstructive shock was documented in 48.9% of cases. Treatment with thrombolytic therapy, surgical thrombectomy, and percutaneous thrombectomy...

Additional file 2 of Successful breastfeeding following a level II NICU stay in Qatar – a longitudinal study

Brijroy Viswanathan, Rajai El Bedaywi, Ahmed Tomerak, Sarfrazul Abedin & Prem Chandra
Additional file 2. Questionnaire.

Registration Year

  • 2022
    70

Resource Types

  • Text
    30
  • Dataset
    26
  • Collection
    14

Affiliations

  • Hamad Medical Corporation
    70
  • Weill Cornell Medical College in Qatar
    48
  • Hamad bin Khalifa University
    44
  • Centre Hospitalier Universitaire de Clermont-Ferrand
    24
  • Memorial Sloan Kettering Cancer Center
    24
  • Sidra Medical and Research Center
    24
  • Cornell University
    24
  • University of Genoa
    20
  • Hamad General Hospital
    20
  • Qatar Foundation
    20